Academic Catalog

BUSI 59D: MARKET ANALYTICS & PERFORMANCE OPTIMIZATION

Foothill College Course Outline of Record

Foothill College Course Outline of Record
Heading Value
Units: 4
Hours: 4 lecture per week (48 total per quarter)
Advisory: BUSI 11; demonstrated proficiency in English by placement via multiple measures OR through an equivalent placement process OR completion of ESLL 125 & ESLL 249.
Degree & Credit Status: Degree-Applicable Credit Course
Foothill GE: Non-GE
Transferable: CSU
Grade Type: Letter Grade (Request for Pass/No Pass)
Repeatability: Not Repeatable

Student Learning Outcomes

  • Demonstrate ability to calculate key marketing metrics and understand their significance to determine strategic marketing optimization decisions.
  • Understand the factors that drive conversion and opportunities to optimize marketing performance.
  • Demonstrate the ability to A/B test various elements of marketing efforts to increase conversion rates.

Description

Focusing on key performance indicators (KPIs), this course aims to give students the skills needed to analyze results of marketing efforts. Students will learn about factors that drive conversion and how to optimize their efforts using data and A/B testing. Students will be assessed through projects that give them an opportunity to get hands-on experience using spreadsheets, Google Analytics and analyzing an A/B test.

Course Objectives

The student will be able to:
A. Understand the factors that drive conversion and opportunities to optimize marketing performance.
B. Demonstrate the ability to A/B test various elements of marketing efforts to increase conversion rates.
C. Demonstrate ability to calculate key marketing metrics and understand their significance to determine strategic marketing optimization decisions.

Course Content

A. Tables, metrics and summaries
1. Spreadsheet basics
2. Key metrics
B. Visualizing data
1. Insights and trends
C. Data analysis
1. Distribution
2. Pivot tables
3. Reporting
D. A/B testing
1. Elements of experimental design
2. Applications
E. Analyzing results
1. Calculating results
2. Significance and hypothesis testing
F. Designing and A/B test
G. Introduction to Google Analytics
H. Reading reports
1. Acquisition reports
2. Behavior reports
I. Optimizing conversions
1. Attribution

Lab Content

Not applicable.

Special Facilities and/or Equipment

A. On-going access to computer with email software and hardware; email address.
B. When taught as an online distance learning section, students and faculty need ongoing and continuous internet and email access.

Method(s) of Evaluation

Methods of Evaluation may include but are not limited to the following:

The student will demonstrate proficiency by participating in the following:
A. Activities
B. Problem-based learning/case studies
C. Demonstration/modeling
D. Discussion
E. Formative quizzes/knowledge checks
F. Performance-based assessments
G. Exams

Method(s) of Instruction

Methods of Instruction may include but are not limited to the following:

During periods of instruction the student will read online lectures and articles, view instructional videos and participate in online activities.

Representative Text(s) and Other Materials

The content for this course is developed and maintained by industry leaders and is open source. There is no textbook comparable.
 

Types and/or Examples of Required Reading, Writing, and Outside of Class Assignments

A. Reading assignments: Students will read articles from industry publishers, such as AdWeek magazine and the Wall Street Journal, and industry websites, such as Google AdWords and Facebook Ad Manager.
B. Writing assignments: Given real-life scenarios, students will analyze customer data and make recommendations.
C. Additional assignments: Students will complete projects designed to practice data modeling, analysis and reporting and calculate key performance metrics.
 

Discipline(s)

Business